Abstract:
In this work we introduce a graph theoretical method to compare MEPs, which is independent of molecular alignment. It is based on the edit distance of weighted rooted trees, which encode the geometrical and topological information of Negative Molecular Isopotential Surfaces. A meaningful chemical classification of a set of 46 molecules with different functional groups was achieved. Structure-activity relationships for the corticosteroid binding affinity (CBG) of 31 steroids by means of hierarchical clustering resulted in a clear partitioning in high, intermediate, and low activity groups, whereas the results from quantitative structure-activity relationships, obtained from a partial least-squares analysis, showed comparable or better cross-validated correlation coefficients than the ones reported for previous methods based solely in the MEP.

Characterization of Activity Landscapes Using 2D and 3D Similarity Methods: Consensus Activity Cliffs
J. Chem. Inf. Model. 2009, 49, 2, 477-491
Jose L. Medina-Franco, Karina Martínez-Mayorga, Andreas Bender, Ray M. Marín, Marc A. Giulianotti, Clemencia Pinilla, Richard A. Houghten

Abstract:
Activity landscape characterization has been demonstrated to be a valuable tool in lead optimization, virtual screening, and computational modeling of active compounds. In this work, we present a general protocol to explore systematically the activity landscape of a lead series using 11 2D and 3D structural representations. As a test case we employed a set of 48 bicyclic guanidines (BCGs) with κ-opioid receptor binding affinity, identified in our group. MACCS keys, graph-based three point pharmacophores, circular fingerprints, ROCS shape descriptors, and the TARIS approach, that compares structures based on molecular electrostatic potentials, were employed as orthogonal descriptors. Based on ‘activity cliffs’ common to a series of descriptors, we introduce the concept of consensus activity cliffs. Results for the current test case suggest that the presence or absence of a methoxybenzyl group may lead to different modes of binding for the active BCGs with the κ-opioid receptor. The most active compound (IC50 = 37 nM) is involved in a number of consensus cliffs making it a more challenge query for future virtual screening than would be expected from affinity alone. Results also reveal the importance of screening high density combinatorial libraries, especially in the “cliff-rich” regions of activity landscapes. The protocol presented here can be applied to other data sets to develop a consensus model of the activity landscape.

Parallel Computing System for the efficient calculation of molecular similarity based on negative electrostatic potential
Raul E. Torres
Master's Thesis, Universidad Nacional de Colombia

Abstract:
This document proposes an alternative method for the comparison of molecular electrostatic potential (MEP), based on parallel computing algorithms on graphics cards using NVIDIA CUDA platform and kernel methods for pattern recognition. The proposed solution optimizes the construction process of a particular representation of MEP, presents options for improving this representation, and offers 11 kernel functions for comparison process. Experimental evaluation using cluster analysis shows good results on a set of 73 molecules from classic chemistry functional groups, finding relationships of acidity and basicity using edit distance and detecting presence of oxygen, nitrogen and functional groups (C=O or C-O) when kernel functions are used.